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cs.LG2026
EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation
Shu-Hao Zhang, Le-Tong Huang, Xiang-Sheng Deng +5
Quantization has emerged as a mainstream approach for deploying Large Language Models (LLMs) on resource-constrained devices, yet compressing precision below 4-bit typically causes…
cs.LG2024★ 1 cited
Exploring Response Uncertainty in MLLMs: An Empirical Evaluation under Misleading Scenarios
Yunkai Dang, Mengxi Gao, Yibo Yan +8
Multimodal large language models (MLLMs) have recently achieved state-of-the-art performance on tasks ranging from visual question answering to video understanding. However, existi…
cs.LG2024
Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models
Kening Zheng, Junkai Chen, Yibo Yan +2
Hallucination issues continue to affect multimodal large language models (MLLMs), with existing research mainly addressing object-level or attribute-level hallucinations, neglectin…